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Fundamentals Of Computer Vision

Fundamentals Of Computer Vision - Qi, Hairong (university Of Tennessee); Snyder, Wesley E. (north Carolina State University) - ISBN: 9781107184886
Prijs: € 113,40
Levertijd: 3 tot 4 werkdagen
Bindwijze: Boek, Gebonden
Genre: Toegepaste webdesign
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This book equips students with crucial mathematical and algorithmic tools to understand complete computer vision systems.


Titel: Fundamentals Of Computer Vision
auteur: Qi, Hairong (university Of Tennessee); Snyder, Wesley E. (north Carolina State University)
Mediatype: Boek
Bindwijze: Gebonden
Taal: Engels
Aantal pagina's: 390
Uitgever: Cambridge University Press
Plaats van publicatie: 03
NUR: Toegepaste webdesign
Afmetingen: 185 x 259 x 24
Gewicht: 946 gr
ISBN/ISBN13: 9781107184886
Intern nummer: 38885495

Biografie (woord)

Hairong Qi is the Gonzalez Family Professor of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville. Her research interests include collaborative signal and image processing, hyperspectral imaging, and bioinformatics. She is the recipient of a National Science Foundation CAREER Award, numerous best paper awards at international conferences, and was awarded the highest impact paper from the Institute of Electrical and Electronics Engineers (IEEE) Geoscience and Remote Sensing Society in 2012.


'Written with depth and clarity, this book introduces a variety of fundamentals needed to participate in computer vision research. Not only does it focus on mathematical fundamentals, but it shows all with well-motivated, concrete examples and applications. I believe vision students and researchers will find this book valuable. I look forward to teaching from it.' Tianfu Wu, North Carolina State University


Part I. Preliminaries: 1. Computer vision, some definitions, and some history; 2. Writing programs to process images; 3. Review of mathematical principles; 4. Images – representation and creation; Part II. Preprocessing: 5. Kernel operators; 6. Noise removal; 7. Mathematical morphology; Part III. Image Understanding: 8. Segmentation; 9. Parametric transforms; 10. Representing and matching shape; 11. Representing and matching scenes; Part IV. The 2-D Image in a 3-D World: 12. Relating to three dimensions; 13. Developing computer vision algorithms.


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